(1) Field of Invention
The present invention relates to a system for inferring the location of users in online social media platforms and, more particularly, to a system for inferring the location of users in online social media platforms using social network analysis.
(2) Description of Related Art
Social media provides a new data source for observing the rapidly changing focus of public interests. Detecting the location from which a message originates provides a powerful way of aggregating content spatially. This spatial focus enables detecting regional differences, detecting emerging trends specific to regions, or even measuring information flow. However, little content is connected with ground truth location data.
Several works have examined location inference on the Twitter™ social media platform. Cheng et al. (see the List of Incorporated Cited Literature References, Literature Reference No. 1), Mahmud et al. (see Literature Reference No. 6), and Ikawa et al. (see Literature Reference No. 5) have examined using the text content produced by a user for inferring their location. While this has produced good results, the approach is limited to only those users who generated text that contained geographic references. Furthermore, their approaches were only tested on English.
Sadilek et al. (see Literature Reference No. 9) perform social network inference in order to estimate the user's true location. However, their approach requires that both users' locations be known in order to estimate the social relationship, which limits the approach to only those individuals with known locations.
Davis Jr. et al. (see Literature Reference No. 2) use a user's follower network in Twitter™ to perform location inference. They use only one round of standard label propagation to infer the location, which can result in limited coverage. Furthermore, their work was tested only on a small set of users, so whether their work is generalizable to larger sets of users remains untested.
Hetch et al. (see Literature Reference No. 4) and Pontes et al. (see Literature Reference No. 8) infer user locations from self provided location information in Twitter™ and FourSquare™, respectively. While Pontes et al. (see Literature Reference No. 8) reported more than 90% coverage of users with this method, no attempt was made to infer the locations of the remaining users. Hetch et al. (see Literature Reference No. 4) found significantly less information in Twitter™ with a high error rate.
Each of the prior methods described above exhibit limitations that make them incomplete. Thus, a continuing need exists for a method for inferring a user's location from their social network and a small amount of ground truth data using an inferred social network designed to maximize the location inference accuracy.